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Anupam Mishra

Graduate Student at University of Southern California

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Anupam Mishra

About Me

I am a highly ambitious and self motivated individual and aim to be an efficient problem solver. I am currently a Graduate Student in Computer Science at University of Southern California, Los Angeles. I have had my fair share of exposure at Oracle and Gozocabs in India and TestMax in USA .My projects in my undergraduate degree and projects at the above mentioned internships had me interface with technologies like, MVC, Cloud Computing (PaaS, SaaS) and I am well versed with Ruby (RoR), Java, Python and also love to work with JavaScript, Node.js and Angular (2/4). With the move to California, I have found my love for biking and hiking.

Experience

TestMax Inc.

Software Engineering Intern

  • Developed a RESTful API for TestMax suite of apps and deployed on AWS using EC2.
  • Integrated the AVATAX Taxation API and Stripe Payment API in the TestMax Web Store and API.
  • Scripted Cron jobs to build premium download and update packages for TestMax suite of apps. These tasks brought down the content refresh time on mobile apps to 93 milliseconds at app launch.
  • Integrated Amazon SES for sending out promotional, transactional and account management emails to users and S3 to store user data.
  • Implemented custom JWT authentication and custom adapter (Rails) for multiple databases for TestMax API.

Gozocabs

Software Engineering Intern

  • Designed and Implemented Broadcast Messaging Module (SMS, Email, Push Notification on Android App) for Admin panel of www.gozocabs.com
  • Collaborated in a team to create a WhatsApp Bot to parse chat data to a database and perform NLP to generate customer and vendor leads.
  • Scripted cron jobs to aggregate daily feedback and communication to vendors and drivers that reduced manual effort to consoli- date and share feedback.
  • Determined and Implemented open source solutions for Customer Ticket Management (OS Tickets) and Business Insights (SpagoBI) modules.

Oracle

Software Engineering Intern

  • Worked on Oracle Application Container Cloud Service, which is based on Docker container.
  • Enhanced the Oracle Java Cloud Service UI.
  • Contributed to build and setup automation of UI project and created required documentation for incoming developers and new hires

Education

University of Southern California

Aug 2017 - May 2019

Master of Science in Computer Science

Relevant Coursework:

Gautam Buddha University

Jul 2012 - May 2017

Integrated B.Tech + M.Tech in Computer Science (Specialization: Software Engineering)

Projects

Personal Stock Portfolio

Developed Web Services and Android Application for Stock Portfolio management using Node.js on Amazon Web Services. Along with Angular 4 used HighCharts API to render indicator and historical price charts of a stock. Containerized the back-end using Docker.

Containerized Backend | Web Application | Android Application

Learners Dashboard

Created a Responsive Web Application that allows users to attempt questions that are fetched in a JSON format. User choices for each question are stored using HTML5 Local Storage. It also provides a comprehensive analysis of the user’s performance and lets the user review his answers after the end of the quiz. Deployed using AWS (S3).

View Project

Student Result Processing System

Led a team of five students to create an online result management portal for faculty at Gautam Buddha University, with functionalities of cloud backup, restore, analytics of student grades and class performance.

View Project

Machine Learning Projects

Implemented the following Machine Learning Algorithms using Python: Decision Tree (ID3), K-Means, Gaussian Mixture Models (using Expectation Maximization),Linear Regression, Linear Classification Logistic Regression, Viterbi Algorithm (HMM), Support Vector Machines, Feed Forward Neural Network, Pocket Algorithm, FastMap, Principal Component Analysis for Dimensionality Reduction. Also, I researched on the available software packages and also implemented the above algorithms using scikit-learn and keras(for NN).

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Twitter Sentiment Classification using a Hybrid Classifier

Implemented a Hybrid Classifier using kNN and SVM machine learning algorithms for Sentiment Classification of Twitter data using Python, Twitter API.

Skills